Instructions to use CSWRY/SeeSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CSWRY/SeeSR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CSWRY/SeeSR", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e8f9ef5093703443aab6acfe987ed1a11cc407f2d7710683ded08b6edd6c2b7
- Size of remote file:
- 7.19 MB
- SHA256:
- a7028be2edcbe9ab0bd1c4ab6f2a2a86f4b44d32261a4faa50ae10fdd9b2feba
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